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Record W2599211905 · doi:10.1021/acs.jafc.7b00326

Formation of a Multiligand Complex of Bovine Serum Albumin with Retinol, Resveratrol, and (−)-Epigallocatechin-3-gallate for the Protection of Bioactive Components

2017· article· en· W2599211905 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Interaction Studies and Fluorescence Analysis
Canadian institutionsUniversity of Alberta
FundersGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsResveratrolBovine serum albuminChemistryEpigallocatechin gallateGallateCircular dichroismSerum albuminBiochemistryPolyphenolChromatographyAntioxidantNuclear chemistry

Abstract

fetched live from OpenAlex

Clarification of the interaction mechanisms between proteins and bioactive components is important to develop effective carriers for encapsulation and protection of bioactive components. Bovine serum albumin (BSA), a globular protein in serum and milk, contains multiple sites to bind a variety of low-molecular-weight molecules, forming protein-monoligand complexes. In this study, the interactions of BSA with retinol, resveratrol, and/or (-)-epigallocatechin-3-gallate (EGCG) were investigated by using fluorescence, circular dichroism, and molecular docking techniques. BSA-triligand complexes were successfully formed when added in the sequence of retinol, resveratrol, and EGCG. The stability of these bioactive components was improved in the complexes relative to free ones. The complexes provided a better protective effect on retinol and resveratrol than did BSA-monoligand complexes, in which the presence of EGCG played an important role.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.240
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it